Interpretable analysis of remote sensing image recognition of vehicles in the complex environment

Yuxin Huo; Yizhuo Ai; Chengqiang Zhao; Yuanwei Li

doi:10.1117/12.2653489

8 December 2022 Interpretable analysis of remote sensing image recognition of vehicles in the complex environment

Yuxin Huo, Yizhuo Ai, Chengqiang Zhao, Yuanwei Li

Proceedings Volume 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022); 124742M (2022) https://doi.org/10.1117/12.2653489
Event: Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 2022, Guilin, China

Abstract

Deep learning technology has yielded good results in remote sensing image recognition of vehicles, but most existing recognition network models have poor interpretability, which limits its wide application. In order to achieve effective detection and recognition of vehicles in the complex environment, in this paper, the YOLOv4 is adopted to realize remote sensing images for vehicle target recognition. In addition, the optimized interpretation method with LIME is used to interpret the recognition results, improving the credibility of the recognition results.

Citation Download Citation

Yuxin Huo, Yizhuo Ai, Chengqiang Zhao, and Yuanwei Li "Interpretable analysis of remote sensing image recognition of vehicles in the complex environment", Proc. SPIE 12474, Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), 124742M (8 December 2022); https://doi.org/10.1117/12.2653489

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